11,243 research outputs found
Computing Motion Plans for Assembling Particles with Global Control
We investigate motion planning algorithms for the assembly of shapes in the
\emph{tilt model} in which unit-square tiles move in a grid world under the
influence of uniform external forces and self-assemble according to certain
rules. We provide several heuristics and experimental evaluation of their
success rate, solution length, runtime, and memory consumption.Comment: 20 pages, 12 figure
Deep learning for unsupervised domain adaptation in medical imaging: Recent advancements and future perspectives
Deep learning has demonstrated remarkable performance across various tasks in
medical imaging. However, these approaches primarily focus on supervised
learning, assuming that the training and testing data are drawn from the same
distribution. Unfortunately, this assumption may not always hold true in
practice. To address these issues, unsupervised domain adaptation (UDA)
techniques have been developed to transfer knowledge from a labeled domain to a
related but unlabeled domain. In recent years, significant advancements have
been made in UDA, resulting in a wide range of methodologies, including feature
alignment, image translation, self-supervision, and disentangled representation
methods, among others. In this paper, we provide a comprehensive literature
review of recent deep UDA approaches in medical imaging from a technical
perspective. Specifically, we categorize current UDA research in medical
imaging into six groups and further divide them into finer subcategories based
on the different tasks they perform. We also discuss the respective datasets
used in the studies to assess the divergence between the different domains.
Finally, we discuss emerging areas and provide insights and discussions on
future research directions to conclude this survey.Comment: Under Revie
Stray Flux Monitoring and Multi-Sensor Fusion Condition Monitoring for Squirrel Cage Induction Machines
This research work investigates the ability of external magnetic flux-based condition monitoring to detect rotor-related faults and incipient stage bearing faults in squirrel-cage induction machines (SCIMs). This work also discusses the multisensory synergy of the external magnetic flux measurement with other measurements. To investigate the stray flux-based monitoring technique, this dissertation presents a theoretical analysis of the characteristic components in the stray flux spectrum of SCIMs as well as experimental validations. A wavelet packet decomposition (WPD) denoising method is proposed for flux-based incipient bearing fault detection.
Additionally, a sensor fusion method to efficiently utilize the information from heterogeneous sensor measurements (external magnetic flux and stator current) to achieve higher rotor-related fault detection sensitivity and a higher fault type recognition rate is presented. Instead of using all the characteristic components directly, the proposed fusion method groups the features of several rotor abnormalities and then draws a conclusion on machine health status based on the abnormalities that are present in the machine.
Finally, a novel sensor fusion-based rotor vibration observer method is proposed for incipient bearing fault detection. The observer can reject the electrical disturbances from the supply side. Meanwhile, the proposed observer is less affected by the mechanical noise from lousy environment than using vibration-based monitoring.Ph.D
Effect of polydispersity in concentrated magnetorheological fluids
Magnetorheological fluids (MRF) are smart materials of increasing interest
due to their great versatility in mechanical and mechatronic systems. As main
rheological features, MRFs must present low viscosity in the absence of a
magnetic field (0.1 - 1.0 Pa.s) and high yield stress (50 - 100 kPa) when
magnetized, in order to optimize the magnetorheological effect. Such
properties, in turn, are directly influenced by the composition, volume
fraction, size, and size distribution (polydispersity) of the particles, the
latter being an important piece in the improvement of these main properties. In
this context, the present work aims to analyze, through experiments and
simulations, the influence of polydispersity on the maximum packing fraction,
on the yield stress under field (on-state), and on the plastic viscosity in the
absence of field (off-state) of concentrated MRF (phi = 48.5 vol.%). Three
blends of carbonyl iron powder in polyalphaolefin oil were prepared. These
blends have the same mode, but different polydispersity indexes, ranging from
0.46 to 1.44. Separate simulations show that the random close packing fraction
increases from about 68% to 80% as the polydispersity index increases over this
range. The on-state yield stress, in turn, is raised from 30 +/- 0.5 kPa to 42
+/- 2 kPa (B ~ 0.57 T) and the off-state plastic viscosity, is reduced from 4.8
Pa.s to 0.5 Pa.s. Widening the size distributions, as is well known in the
literature, increases packing efficiency and reduces the viscosity of
concentrated dispersions, but beyond that, it proved to be a viable way to
increase the magnetorheological effect of concentrated MRF. The Brouwers model,
which considers the void fraction in suspensions of particles with lognormal
distribution, was proposed as a possible hypothesis to explain the increase in
yield stress under magnetic field
Countermeasures for the majority attack in blockchain distributed systems
La tecnología Blockchain es considerada como uno de los paradigmas informáticos más importantes posterior al Internet; en función a sus características únicas que la hacen ideal para registrar, verificar y administrar información de diferentes transacciones. A pesar de esto, Blockchain se enfrenta a diferentes problemas de seguridad, siendo el ataque del 51% o ataque mayoritario uno de los más importantes. Este consiste en que uno o más mineros tomen el control de al menos el 51% del Hash extraído o del cómputo en una red; de modo que un minero puede manipular y modificar arbitrariamente la información registrada en esta tecnología. Este trabajo se enfocó en diseñar e implementar estrategias de detección y mitigación de ataques mayoritarios (51% de ataque) en un sistema distribuido Blockchain, a partir de la caracterización del comportamiento de los mineros. Para lograr esto, se analizó y evaluó el Hash Rate / Share de los mineros de Bitcoin y Crypto Ethereum, seguido del diseño e implementación de un protocolo de consenso para controlar el poder de cómputo de los mineros. Posteriormente, se realizó la exploración y evaluación de modelos de Machine Learning para detectar software malicioso de tipo Cryptojacking.DoctoradoDoctor en Ingeniería de Sistemas y Computació
Eigen-Factors an Alternating Optimization for Back-end Plane SLAM of 3D Point Clouds
Modern depth sensors can generate a huge number of 3D points in few seconds
to be latter processed by Localization and Mapping algorithms. Ideally, these
algorithms should handle efficiently large sizes of Point Clouds under the
assumption that using more points implies more information available. The Eigen
Factors (EF) is a new algorithm that solves SLAM by using planes as the main
geometric primitive. To do so, EF exhaustively calculates the error of all
points at complexity , thanks to the {\em Summation matrix} of
homogeneous points.
The solution of EF is highly efficient: i) the state variables are only the
sensor poses -- trajectory, while the plane parameters are estimated previously
in closed from and ii) EF alternating optimization uses a Newton-Raphson method
by a direct analytical calculation of the gradient and the Hessian, which turns
out to be a block diagonal matrix. Since we require to differentiate over
eigenvalues and matrix elements, we have developed an intuitive methodology to
calculate partial derivatives in the manifold of rigid body transformations
, which could be applied to unrelated problems that require analytical
derivatives of certain complexity.
We evaluate EF and other state-of-the-art plane SLAM back-end algorithms in a
synthetic environment. The evaluation is extended to ICL dataset (RGBD) and
LiDAR KITTI dataset. Code is publicly available at
https://github.com/prime-slam/EF-plane-SLAM
The dynamics and ISM properties of high-redshift dusty star-forming galaxies
In this thesis we present a range of observations of submillimetre galaxies (SMGs), a subclass of dust-obscured star-forming galaxies (DSFGs) at redshifts of z~1-5. SMGs are among the most actively star forming sources ever observed, believed to contribute significantly to the star-formation rate density (SFRD) at its peak, so-called 'cosmic noon', at z~2. Given their extreme nature, SMGs provide a strong test of galaxy formation and evolution models. Advancements in instrumentation, in particular with the Submillimetre Common-User Bolometer Area 2 (SCUBA-2) and the Atacama Large (sub-)Millimeter Array (ALMA), have driven significant progress in SMGs studies over the last decade. We have now identified samples of hundreds of SMGs in survey fields with a plethora of photometric coverage, such as the Cosmic Evolution Survey (COSMOS), the UKIDSS Ultra Deep Survey (UDS) and the Extended Chandra Deep Field Survey (ECDFS). Indeed, the main motivation of this thesis is to exploit these samples of SMGs, with a particular focus on the molecular and ionised gas properties, using state-of-the-art instrumentation such as ALMA and the Northern Extended Millimeter Array (NOEMA) for the former, and the K-band Multi-Object Spectrograph (KMOS) mounted on the Very Large Telescope for the latter.
Firstly, in Chapter 2 we present CO observations of 47 SMGs, providing one of the largest and highest quality samples of its kind. With this study we demonstrate the capability of ALMA and NOEMA to undertake blind redshift scans in the 3mm waveband, and in doing so add significantly to the number of SMGs with spectroscopic redshifts, which prior to the work presented in this thesis was small. We also exploit the multi-wavelength coverage of the samples, together with the robust new spectroscopic redshifts, to model their spectral energy distributions (SEDs) with the MAGPHYS code and subsequently estimate key physical properties such as stellar masses and star-formation rates.
Perhaps more importantly, this survey has allowed us to characterise the molecular gas content in the SMG population, along with its excitation properties, results from which we present in Chapter 3. We also show that the gas depletion timescale in SMGs remains constant, and given that SMGs are significant contributors to the star-formation rate density (SFRD) at z~2, the global evolution of star-formation in SMGs appears to coincide with the evolution of the molecular gas content, as opposed to any variation in star-formation efficiency. We provide a new test of the SMG population as descendants of massive local early-type galaxies, using the derived CO linewidths and baryonic masses.
In Chapter 4 we present our Large Programme with KMOS which, when completed, will have observed ~400 SMGs in the COSMOS, UDS and ECDFS fields. Expanding on the work of Chapters 2 and 3 this is designed to further add to the catalog of SMGs with spectroscopic redshifts by detecting the H_alpha and/or [OIII] emission, which probes ionised gas and can also be used to estimate star-formation rates. We detail the target selection and observing strategy of this survey, before presenting early results for 43 emission line-detected sources, including the H_alpha-derived star-formation rates, the mass-metallicity relation and BPT diagram. We also compare the H_alpha, rest-frame optical/near-infrared and dust sizes where available, finding median radii of R_e = 3.6+/-0.3 kpc, R_Halpha = 4.2+/-0.4 kpc and R_dust = 1.2+/-0.3 kpc. Additionally, the sample are consistent with a median Sersic index of n=1, i.e. with an exponential disc-like light profile.
The integral field spectrograph (IFS) capabilities of KMOS allow us to spatially resolve the H_alpha/[OIII] emission when it is sufficiently bright and extended, and this provides valuable diagnostics of the galaxy kinematics. Therefore, in Chapter 5 we present resolved H_alpha/[OIII] velocity and velocity dispersion maps for 36 SMGs, from which we derive rotation curves and dispersion profiles. We compare the derived kinematics of our SMGs with less active galaxies at lower redshifts, and divide the sample into 28 'ordered' sources with clear velocity gradients, and rotation curves which can be modelled as Freeman disks, and eight 'disordered' sources with much more messy velocity maps, from which little reliable kinematic information can be obtained. We measure a median rotational velocity of v_rot = 190+/-20 km/s and a median intrinsic velocity dispersion of sigma_0 = 87+/-5 km/s from the 'ordered' subset, both of which are significantly higher than the less actively star-forming galaxies to which we compare. The median ratio of rotational velocity to intrinsic velocity dispersion in the 'ordered' sample is v_rot/sigma_0 = 2.2+/-0.5, indicating that our sources are somewhat rotationally supported, and we therefore suggest that our SMG sample likely represents 'scaled-up' versions of more 'normal' star-forming galaxies, rather than merger-dominated systems
A design approach for controlled blade-off in overspeeding turbines
Following a shaft failure or loss of load in a gas turbine engine, the turbine overspeeds due to the continuing expansion through the stage(s). The overspeed may result in hazardous conditions which have to be prevented. Several mitigation methods include the control system’s response by shutting the fuel flow, mechanical friction to reduce turbine acceleration, and blade release at a predetermined rotational speed. The release of the blades not only terminates the gas torque which accelerates the disk, but also increases the disk burst speed at reduced centrifugal load. In this manuscript, a design space exploration is presented to avoid disk burst by blade-off in a civil large turbofan engine through a parametric design of blade firtree and disk post system. The firtree design parameters used in the study are the contact angle between the blade firtree and the disk post, firtree bottom flank angle, firtree flank length and firtree thickness with respect to the disk post. The LS-DYNA finite element software was used in the simulations to generate possible failure scenarios. These were ‘disk burst’ and ‘blade-off’. Blade-off conditions manifested in two ways as a function of design parameters. The first type was blade release from serrations without disk post failure, and the second type was blade escape with disk post failure. Following the design space exploration, the effect of several design and material parameters on the design space was investigated. These parameters are; the contact friction coefficient between the blade firtree and disk post, firtree serration number, and the strain hardening behavior of the material
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